A heavy rainfall case related to Mesoscale Convective Systems (MCSs) over the Korean Peninsula was selected to investigate the impact of radar data assimilation on a heavy rainfall forecast. The Weather Research and...A heavy rainfall case related to Mesoscale Convective Systems (MCSs) over the Korean Peninsula was selected to investigate the impact of radar data assimilation on a heavy rainfall forecast. The Weather Research and Forecasting (WRF) three-dimensional variational (3DVAR) data assimilation system with tuning of the length scale of the background error covariance and observation error parameters was used to assimilate radar radial velocity and reffectivity data. The radar data used in the assimilation experiments were preprocessed using quality-control procedures and interpolated/thinned into Cartesian coordinates by the SPRINT/CEDRIC packages. Sensitivity experiments were carried out in order to determine the optimal values of the assimilation window length and the update frequency used for the rapid update cycle and incremental analysis update experiments. The assimilation of radar data has a positive influence on the heavy rainfall forecast. Quantitative features of the heavy rainfall case, such as the maximum rainfall amount and Root Mean Squared Differences (RMSDs) of zonal/meridional wind components, were improved by tuning of the length scale and observation error parameters. Qualitative features of the case, such as the maximum rainfall position and time series of hourly rainfall, were enhanced by an incremental analysis update technique. The positive effects of the radar data assimilation and the tuning of the length scale and observation error parameters were clearly shown by the 3DVAR increment.展开更多
This study investigated the impact of multiple-Doppler radar data and surface data assimilation on forecasts of heavy rainfall over the central Korean Peninsula;the Weather Research and Forecasting(WRF) model and its ...This study investigated the impact of multiple-Doppler radar data and surface data assimilation on forecasts of heavy rainfall over the central Korean Peninsula;the Weather Research and Forecasting(WRF) model and its three-dimensional variational data assimilation system(3DVAR) were used for this purpose. During data assimilation,the WRF 3DVAR cycling mode with incremental analysis updates(IAU) was used. A maximum rainfall of 335.0 mm occurred during a 12-h period from 2100 UTC 11 July 2006 to 0900 UTC 12 July 2006.Doppler radar data showed that the heavy rainfall was due to the back-building formation of mesoscale convective systems(MCSs).New convective cells were continuously formed in the upstream region,which was characterized by a strong southwesterly low-level jet(LLJ).The LLJ also facilitated strong convergence due to horizontal wind shear,which resulted in maintenance of the storms.The assimilation of both multiple-Doppler radar and surface data improved the accuracy of precipitation forecasts and had a more positive impact on quantitative forecasting(QPF) than the assimilation of either radar data or surface data only.The back-building characteristic was successfully forecasted when the multiple-Doppler radar data and surface data were assimilated.In data assimilation experiments,the radar data helped forecast the development of convective storms responsible for heavy rainfall,and the surface data contributed to the occurrence of intensified low-level winds.The surface data played a significant role in enhancing the thermal gradient and modulating the planetary boundary layer of the model,which resulted in favorable conditions for convection.展开更多
OBJECTIVE:To investigate the molecular effect of Socheongryong Tang(SCRT,Xiaoqinglong Tang in Chinese) on whole genome level in asthma mouse model by microarray technology.METHODS:Asthma was induced by intranasal inst...OBJECTIVE:To investigate the molecular effect of Socheongryong Tang(SCRT,Xiaoqinglong Tang in Chinese) on whole genome level in asthma mouse model by microarray technology.METHODS:Asthma was induced by intranasal instillation of ovalbumin in mouse.After administration of SCRT on asthma-induced mouse,the expression of genes in lung tissue was measured using whole genome microarray.The functional implication of differentially expressed genes was performed using ontological analysis and the similarity of promoter structure of genes was also analyzed.RESULTS:Treatment of SCRT restored expression level of many up- or down-regulated genes in asthma model,and this recovery rate means SCRT could regulate a set of genes having specific TFBS binding sites.CONCLUSION:In this study,we identified a set of genes subjected to similar regulation by SCRT in asthma model in mice.展开更多
基金supported by the Korea Meteorological Administration Research and Development Program under Grant CATER 2006–2303 and by the Brain Korea 21 Project in 2007
文摘A heavy rainfall case related to Mesoscale Convective Systems (MCSs) over the Korean Peninsula was selected to investigate the impact of radar data assimilation on a heavy rainfall forecast. The Weather Research and Forecasting (WRF) three-dimensional variational (3DVAR) data assimilation system with tuning of the length scale of the background error covariance and observation error parameters was used to assimilate radar radial velocity and reffectivity data. The radar data used in the assimilation experiments were preprocessed using quality-control procedures and interpolated/thinned into Cartesian coordinates by the SPRINT/CEDRIC packages. Sensitivity experiments were carried out in order to determine the optimal values of the assimilation window length and the update frequency used for the rapid update cycle and incremental analysis update experiments. The assimilation of radar data has a positive influence on the heavy rainfall forecast. Quantitative features of the heavy rainfall case, such as the maximum rainfall amount and Root Mean Squared Differences (RMSDs) of zonal/meridional wind components, were improved by tuning of the length scale and observation error parameters. Qualitative features of the case, such as the maximum rainfall position and time series of hourly rainfall, were enhanced by an incremental analysis update technique. The positive effects of the radar data assimilation and the tuning of the length scale and observation error parameters were clearly shown by the 3DVAR increment.
基金supported by the Global Partnership Program of the Korea Foundation of International Cooperation for Science and Technology(KICOS)the Korea Meteorological Administration Research and Development Program under Grant RACS 2010-2016This research was also supported by the BK21 program of the Korean Government Ministry of Education.
文摘This study investigated the impact of multiple-Doppler radar data and surface data assimilation on forecasts of heavy rainfall over the central Korean Peninsula;the Weather Research and Forecasting(WRF) model and its three-dimensional variational data assimilation system(3DVAR) were used for this purpose. During data assimilation,the WRF 3DVAR cycling mode with incremental analysis updates(IAU) was used. A maximum rainfall of 335.0 mm occurred during a 12-h period from 2100 UTC 11 July 2006 to 0900 UTC 12 July 2006.Doppler radar data showed that the heavy rainfall was due to the back-building formation of mesoscale convective systems(MCSs).New convective cells were continuously formed in the upstream region,which was characterized by a strong southwesterly low-level jet(LLJ).The LLJ also facilitated strong convergence due to horizontal wind shear,which resulted in maintenance of the storms.The assimilation of both multiple-Doppler radar and surface data improved the accuracy of precipitation forecasts and had a more positive impact on quantitative forecasting(QPF) than the assimilation of either radar data or surface data only.The back-building characteristic was successfully forecasted when the multiple-Doppler radar data and surface data were assimilated.In data assimilation experiments,the radar data helped forecast the development of convective storms responsible for heavy rainfall,and the surface data contributed to the occurrence of intensified low-level winds.The surface data played a significant role in enhancing the thermal gradient and modulating the planetary boundary layer of the model,which resulted in favorable conditions for convection.
文摘OBJECTIVE:To investigate the molecular effect of Socheongryong Tang(SCRT,Xiaoqinglong Tang in Chinese) on whole genome level in asthma mouse model by microarray technology.METHODS:Asthma was induced by intranasal instillation of ovalbumin in mouse.After administration of SCRT on asthma-induced mouse,the expression of genes in lung tissue was measured using whole genome microarray.The functional implication of differentially expressed genes was performed using ontological analysis and the similarity of promoter structure of genes was also analyzed.RESULTS:Treatment of SCRT restored expression level of many up- or down-regulated genes in asthma model,and this recovery rate means SCRT could regulate a set of genes having specific TFBS binding sites.CONCLUSION:In this study,we identified a set of genes subjected to similar regulation by SCRT in asthma model in mice.